SubgroupTE: Advancing Treatment Effect Estimation with Subgroup Identification
SubgroupTE:结合子群识别的治疗效应估计
Precise estimation of treatment effects is crucial for evaluating intervention effectiveness. While deep learning models have exhibited promising performance in learning counterfactual representations for treatment effect estimation (TEE), a major limitation in most of these models is that they treat the entire population as a homogeneous group, overlooking the diversity of treatment effects across potential subgroups that have varying treatment effects. This limitation…